New Delhi, Aug. 6 -- Databases are critical to modern operations, underpinning nearly every online service, retail transaction, and medical procedure. Today, a resurgence in database technology is being driven by artificial intelligence (AI) and a hybrid cloud environment, leading to challenges like data overload and cybersecurity threats that necessitate modern data platforms. In an interview with TechCircle, Jenny Tsai, senior vice president, Overall Database Product Management at U.S.-headquartered technology company Oracle, said that addressing these challenges demands technological solutions, robust processes, and skilled personnel.
As Oracle significantly shaped the evolution of this technology over the years, Tsai, an Oracle veteran for three decades, highlighted Oracle's successful transition to the cloud while continuing on-premises data management. Elaborating on the shift, Tsai said that the Oracle Autonomous Database is a major advancement, moving past traditional systems that required manual intervention and were prone to inefficiencies and vulnerabilities. The cloud paved the way for flexible solutions, but autonomous databases unlocked the potential of AI-driven data management. At the same time, despite cloud adoption, many large businesses still rely on on-site data centres and mainframes due to the difficulty of migration.
"In recent years, we've been expanding our reach through other cloud hyperscalers with our database system available across all major cloud platforms (AWS, Google, Azure), said Tsai, emphasising that Oracle Database is ubiquitous, as it is available essentially in all the hyperscaler clouds plus On-premises, including IBM-AIX and Linux, etc. This offers a choice to our customers," said Tsai.
The company has also packed a lot more capabilities, leveraging AI and machine learning, to ensure that the management of the database, in terms of upgrading, patching, tuning, troubleshooting, and so forth, is done autonomously. As Tsai noted that organisations are increasingly adopting converged databases for managing diverse data types in a unified environment. Oracle Database 23ai, released last year, exemplifies this, she said, allowing enterprises to train and deploy machine learning models within their database infrastructure, automate security monitoring, and optimise workloads with AI.
"Oracle Database 23ai integrates AI at its core, transforming data handling, security, and optimisation. Its AI Vector Search enables rapid indexing and similarity searches across various data types. Machine learning integration allows businesses to build AI-enabled applications. Furthermore, the database employs AI to fine-tune operations, providing smarter predictions for resource usage and simplifying tasks," she said.
Oracle also focuses on collaboration and integration with open-source technologies like Apache Iceberg and vector databases. Its annually updated Exadata system offers differentiated advantages, optimising Oracle Database to leverage hardware and specialised storage software for accelerated vector processing and index creation.
Customers can utilise AI through public cloud services or private models, ensuring data privacy. Oracle is exploring xAI and open-source AI models to expedite debugging and improve code for long-standing products. Tsai stated that internally, AI aids product development and engineering teams, accelerating documentation and technical brief creation. Oracle is also developing AI solutions to grade presentations and enhance storytelling.
Furthermore, data quality and governance are crucial, as Tsai believes that Oracle leverages its extensive experience to ensure data quality and incorporates capabilities into its Autonomous Database Service for end-to-end data lineage tracking. This includes tracking data origin and usage. The Oracle database also provides data pipelines for AI training.
Tsai further noted that CIOs prioritise cost reduction, faster time-to-market, and risk mitigation. Oracle aims to align its product capabilities with these needs, with a deeper focus on Agentic AI. She advises organisations to prioritise data quality, security, and governance to maintain reliable, secure, and effective databases. "This technology aims to enable AI to intelligently perform tasks, dynamically assessing and executing each step, promising cost-effectiveness, enhanced safety, and faster execution," she said.
Looking ahead, AI will serve as an assistant - not a replacement - freeing CIOs and database administrators from repetitive manual tasks so they can concentrate on strategic activities. It will assist them in discovering new ways to utilise data and technology. Ultimately, they will be able to use AI to improve their roles and make more strategic contributions to their companies.
Published by HT Digital Content Services with permission from TechCircle.